CN1231409C - Optimum managing method for elevator group - Google Patents

Abstract

The present invention provides an elevator group optimum supervisory operation method capable of performing an optimum car operation, an easy call assignment calculation and a high speed calculation and system thereof. In this elevator group optimum supervisory operation method and system thereof, an elevator is efficiently operated by calling an element on a matrix in the relation of a departure floor and an arrival floor that an elevator car is capable of performing service as a mission unit, calling combinations in the mission unit that an elevator is capable of performing service one time as a mission group, calling a set of the mission groups prepared with respect to the whole of the elevator group as a mission group set and dynamically imparting the mission group set to the elevator group.

Description

The optimum management method and system of elevator group

Technical field

The present invention relates in comprising the elevator device of a plurality of elevator car, move the optimum management method and system of the elevator group of these elevator car expeditiously.

Background technology

The purpose of the optimum management method and apparatus of elevator group is to move the elevator device of many elevator car expeditiously, has therefore improved the excellent service standard in the building that is provided with this elevator device.For this reason, when passenger (user) when platform is pressed the calling of call button generation platform of the platform that is used to call out elevator, the optimum management method and apparatus of elevator group is considered the excellent service standard that improves the bed rearrangement building, the terraced railway carriage or compartment of the calling of described platform is replied in decision from many elevator car, carries out call distribution.

But, in this call distribution mode, can not correctly predict calling in the future.For this reason, people attempt to combine by the terraced railway carriage or compartment operation rule and the call distribution mode that will be suitable for flow of traffic with the preparation allocation scheme, improve traffic capacity.Below, we will contrast the mode that terraced railway carriage or compartment operation rule that flow of traffic decision is suitable for flow of traffic moves and be called " operation mode ".

In this operation mode, in very many work hours sections of passenger etc., service floor is divided into several zones.In addition, be predetermined the terraced railway carriage or compartment of being responsible for each zone.Therefore, divide the zone (cut apart drive manner) of elevator under each floor that will go, just may improve operating efficiency by making passenger from main floor.Such Region Segmentation drive manner is published on the patent 2-43188 communique that Japan puts down into 2 years.

These existing mode whichevers all are divided into several zones with many floors.For this reason, be resultful for flow of traffic with more simple feature such as working.But,, be difficult thereby provide actv. to cut apart drive manner raising operating efficiency for having the more flow of traffic of complex features.In addition, in existing mode, the Region Segmentation mode only to certain specific flow of traffic and with its similar flow of traffic be actv.., corresponding to diversified flow of traffic, must sound out ground and generate for the region segmentation method of each flow of traffic and the rule of distribution method, it is very difficult automatically generating such rule.

Summary of the invention

In order to address this is that, in the optimum management method and apparatus of elevator group of the present invention, the conveying business that each elevator carries out is by constituting to service unit that another arrival floor is carried (below, be called " task unit ") from 's floor.These service units are divided into a plurality of business sheet hytes (below, be called " task groups ").In addition, the business sheet hyte is dynamically distributed to terraced railway carriage or compartment.As a result, for diversified flow of traffic, traffic capacity and operating efficiency have been improved.In addition, can generate the unified rule that turns round of cutting apart.Further, by the gimmick and the combination of optimizationization, can automatically generate the rule (that is task groups) that improves traffic capacity and operating efficiency.

Particularly, optimum management method according to elevator group of the present invention is the optimum management method of the elevator group of a plurality of elevator car of operation, in the method, an element on the row-column list that concerns between floor and the arrival floor that sets out that may serve of expression elevator car is called task unit, the combination of the task unit that an elevator once may be served is called task groups, to be called the task groups set for the set of all task groups of preparing of elevator group, thereby move elevator expeditiously by elevator group is dynamically distributed in this task groups set.

Feature according to the optimum management method of the elevator group of other form of the present invention is to infer occurent flow of traffic, for the flow of traffic of inferring, and the task groups that decision is optimized, the task groups that will belong to this task groups set is dynamically distributed to a plurality of elevators.

Feature according to the optimum management method of the elevator group of other form of the present invention is to infer occurent flow of traffic, for the flow of traffic of inferring, carry out the assessment of task groups set, the task groups set that decision is optimized, the task groups that will belong to the task groups set of this optimization is dynamically distributed to a plurality of elevators.

Feature according to the optimum management method of the elevator group of other form of the present invention is to infer occurent flow of traffic, for the flow of traffic of inferring, by real time simulator task groups set is assessed, the task groups set that decision is optimized, the task groups that will belong to the task groups set of this optimization is dynamically distributed to a plurality of elevators.

According to the optimum management method of the elevator group of other form of the present invention is that the flow of traffic that will once obtain and the relation between the task groups set are stored in the data bank, determine the task groups of optimizing to gather from the result that infers of this data bank and flow of traffic, the task groups that will belong to the task groups set of this optimization is dynamically distributed to the optimum management method that a plurality of elevators are the elevator group of feature.

Feature according to the optimum management method of the elevator group of other form of the present invention is the relation that makes between neural network learning flow of traffic and the task groups, result from neural network learning, the task groups set that decision is optimized, the task groups that will belong to the task groups set of this optimization is dynamically distributed to a plurality of elevators.

The feature of the optimum management system of the elevator group of a plurality of elevator car of operation of the present invention is to have

(a) terraced railway carriage or compartment information detection section, it detects the state of elevator and platform device,

(b) flow of traffic is inferred part, and it infers flow of traffic according to the information that obtains from described terraced railway carriage or compartment information detection section,

(c) task groups set candidate generating portion, it makes the candidate of a plurality of task groups set,

(d) real time simulator, it calculates the assessed value in the task groups set of described real time simulator generation for infer the traffic flow data of inferring that part obtains from described flow of traffic,

(e) task groups set evaluation part, it carries out the assessment to the task groups set according to the assessed value that obtains from described task groups set assessed value calculating section,

(f) task groups set deciding section, it is according to the result of described task groups set evaluation part, and the task groups that decision is optimized is gathered,

(g) task groups set storage area, it will store in the task groups set of described task groups set deciding section decision,

(h) task groups selection part, its is subordinated to the task groups that selection needs at this moment in the task groups that is stored in the task groups set in the described task groups set storage area according to the information that obtains from described terraced railway carriage or compartment information detection section,

(i) task groups distribution portion, it will sub-elect task groups in described task groups selection portion and distribute to terraced railway carriage or compartment,

(j) call distribution part, it gives terraced railway carriage or compartment according to the allocation situation of the task groups that determines in described task groups distribution portion with the call distribution of platform,

(k) terraced railway carriage or compartment control part, it is controlled terraced railway carriage or compartment according to the allocation situation of call distribution part.

Other the feature of optimum management system of elevator group of the present invention is to have according to the data bank of task groups set and be stored in information in the described data bank, selects the task groups set of the task groups set optimized to select part.

Other the feature of optimum management system of elevator group of the present invention is the flow of traffic of inferring by study and to the neural network of the relation between the optimal task groups set of this flow of traffic, selects the neural network task groups set of the task groups set optimized to select part.

Description of drawings

[Fig. 1] is the figure of formation of optimum management method and apparatus of the elevator group of expression example 1 of the present invention.

[Fig. 2] is the figure of the structure of expression OD figure.

[Fig. 3] is the figure of the structure of expression job order bitmap of the present invention.

[Fig. 4] is the figure of the structure of expression task groups set of the present invention.

[Fig. 5] is the figure that the task groups of expression example 1 of the present invention is gathered the formation of generating portion (5).

[Fig. 6] is the figure that the task groups of explanation example 1 of the present invention is gathered the computation sequence of assessed value calculating section (5-2).

[Fig. 7] is the figure that the task groups of expression example 2 of the present invention is gathered the formation of generating portion (5).

[Fig. 8] is the figure of formation of the real time simulator part (5-5) of expression example 2 of the present invention.

[Fig. 9] is the figure of formation of optimum management method and apparatus of the elevator group of expression example 3 of the present invention.

[Figure 10] is the figure of formation of optimum management method and apparatus of the elevator group of expression example 4 of the present invention.

[Figure 11] is the figure that the formation of part (13) is selected in the neural task groups set of expression example 4 of the present invention.

[Figure 12] is the neural network 1 3-2 of expression example 4 of the present invention and the figure that task groups is gathered the formation of selective filter 13-3.

The specific embodiment

Below, we are with reference to a plurality of examples of appended all figure explanations according to the optimum management method and system of elevator group of the present invention.

Example 1

For the various flow of traffics of correspondence, intrinsic notion (" task unit " below the optimum management method and system of elevator group of the present invention imports in this system, " task groups ", " task groups set "), formulate operational plan according to these intrinsic notion plannings.

Here, an elevator car is called " task unit " from 's floor to the service unit of another arrival floor conveying people.When to an elevator car, when representing to set out floor and arrival floor with row-column list (please refer to Fig. 3), this task unit constitutes an element of this row-column list.

In addition, the set of a plurality of task units that the enough terraced railway carriage or compartments of energy are served is called " task groups ".This task groups is as working as to an elevator car, when representing to set out floor and arrival floor with row-column list, comprising the business sheet hyte of distributing to a plurality of task units of this elevator car in the will that do tabulation shows and (please refer to Fig. 4 (a), (b), (c), (d)).

Further, the set of task groups is called task groups set (please refer to Fig. 4 (a), (b), (c), (d)), all services of its expression elevator group.

Therefore, the optimum management method and system of the elevator group of the present application generates a plurality of task groups and task groups set that cooperates flow of traffic, each task groups that will belong to task groups set is dynamically distributed to terraced railway carriage or compartment, matches the operation in each terraced railway carriage or compartment according to the branch of this task groups and controls.

Fig. 1 represents the basic comprising according to the optimum management method and system of the elevator group of example 1.In this drawing, symbol 1-1～1-N is that symbol N is the platform number of lift appliance or elevator car by a plurality of lift appliances (or elevator car) of the optimum management method and system control of this elevator group.Call button 2-1～the 2-H[H of platform: platform number (number of floor levels)] be to specify the platform call button that will remove floor, for example, be the device that has the platform call button that will remove floor, be installed on the suitable position (the normally wall on elevator door next door) of the elevator station of each floor.Ladder railway carriage or compartment information detection section 3 is carried out the position of terraced railway carriage or compartment device 1-1～1-N, speed, last elevator number, call out the registration situation in terraced railway carriage or compartment, allocation situation, operating state, the detection of the information relevant of the state of elevator door etc. and the signal by platform call button 2-1～2-H input with terraced railway carriage or compartment device.Flow of traffic is inferred part 4 according to the information that detects in terraced railway carriage or compartment information detection section 3, and the flow of traffic that takes place in the building that is provided with lift appliance 1-1～1-N is inferred.Inferring the result that part 4 infers at flow of traffic provides the shape of passenger's incidence (people/time) and OD (floor-arrival floor sets out) figure as the traffic flow data of inferring.OD figure is the row-column list that each passenger between floor and the arrival floor of setting out of expression moves ratio, as shown in Figure 2.Task groups set generating portion 5 presumptive traffic flow datas and terraced railway carriage or compartment information generate the task groups set that is used in that flow of traffic.As mentioned above, task groups set is the set of the task groups used in certain flow of traffic.Task groups set storage area 6 is stored in the task groups set that generates in the task groups set generating portion 5.The task groups set selects part 7 to select to provide the calling that takes place the task groups of service.Task groups distribution portion 8 when the task groups of selecting part 7 to select in the task groups set is not distributed to terraced railway carriage or compartment, determines the distribution in terraced railway carriage or compartment.Call distribution part 9 is according to the distribution of task groups, and the terraced railway carriage or compartment of calling is distributed in decision, and sends assignment command to terraced railway carriage or compartment control part 10.Ladder railway carriage or compartment control part 10 is controlled terraced railway carriage or compartment device and display lamp etc. according to the call distribution result.

It more than is the basic composition of the optimum management method and apparatus of elevator group in the present invention, below to the task groups at the center that becomes this formation, with task groups set generating portion 5, task groups set storage area 6, task groups is selected part 7, task groups distribution portion 8, call distribution part 9 is carried out stating of details.

Elevator is to bear the means of conveyance that the passenger moves in the building, and the optimum management method and apparatus of elevator group is the situation occurred according to passenger (user), and the operation of elevator car device 1-1～1-N is managed.Here, passenger's situation occurred is called flow of traffic, this flow of traffic with the passenger of time per unit number takes place and OD figure represents.OD figure is that respectively set out passenger between floor and each arrival floor of as shown in Figure 2 expression moves the row-column list of ratio.In Fig. 2, and OD (i j) is the element of OD figure, and expression is in all passengers that takes place sometime, from (i) floor, and the passenger's who moves to (j) floor ratio.Like this, the least unit of passenger's flow of traffic is the moving between floor (i) and the arrival floor (j) of setting out.Thereby, also can regard the least unit of operation of these passengers' of transportation elevator car as follow floor (i) moving to arrival floor (j).Therefore, as mentioned above, we are called " task unit " with the least unit of the terraced railway carriage or compartment operation that take in a terraced railway carriage or compartment.Task unit is represented with the such figure of Fig. 3.For example, in the situation in the terraced railway carriage or compartment of only having prepared the job order figure place, can think that a terraced railway carriage or compartment is suitable with a task unit.But such situation is non-existent in reality.Therefore, several task units are combined, generate the set (task groups) of the task unit of taking in a terraced railway carriage or compartment.In order to make the operating efficiency maximization,, generate these a plurality of task groups according to flow of traffic and terraced railway carriage or compartment platform number.In addition, dynamically the task groups that generates is distributed to terraced railway carriage or compartment according to the calling that takes place, according to the distribution of task groups, the terraced railway carriage or compartment of decision answering call.Here, as mentioned above, the set of the task groups that generates is called the task groups set.This task groups is gathered and is represented with a plurality of row-column lists shown in Figure 4, as follows fixed patternization.

MGset＝{MG ₁、MG ₂、....、MG _M} (1)

MG _k＝{dm _k(i、j)：dm _k＝1?or?0、i、j＝1、...、L、i≠j}(k＝1、...、M) (2)

Here, MG _kBe k task groups, when k task groups taken on task unit dm (i, dm in the time of j) _k(i j) gets the value of " 1 ", when not taking on dm (i, dm in the time of j) _k(i j) gets the value of " 0 ", and following constraint condition is arranged.

1≤M≤N (3)

$\underset{k=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{dm}}_k(i,j)\≥1---\left(4\right)$

L is a number of floor levels, and N is the platform number in terraced railway carriage or compartment, and M is the task groups number that belongs to the task groups set.For example, in Fig. 4, work as dm ₁(1,7)=1, dm ₂(1,7)=0, dm ₃(1,7)=0, dm ₄(1,7)=0 o'clock, the terraced railway carriage or compartment of only distributing to task groups 1 can be to providing service from 7 layers of mobile passenger of 1 course.

In addition, work as dm ₁(7,1)=1, dm ₂(7,1)=0, dm ₃(7,1)=0, dm ₄(7,1)=1 o'clock, the terraced railway carriage or compartment of distributing to task groups 1 or task groups 4 can be to providing service from 7 layers of mobile passenger of 1 course.

In this example, task groups set generating portion 5 determines the dm of formula (2) like that in order to make the operating efficiency maximization _k(i, value j).

Below, state the dm of formula (2) _k(i, the determining method of each element value j).Fig. 5 represents the formation of task groups set generating portion 5.Task groups set candidate generating portion 5-1 generates and satisfies (3), the candidate group of the task groups set of the constraint condition of (4).Here, the following expression of (p) individual task groups set candidate.

MGset _p＝{MG _p，1，MG _p，2，...，MG _p，M，} (p＝1、....、P) (5)

MG _p、k＝{dm _p、k(i、j)：(i、j)i、j＝1、...、L、i≠j} (k＝1、...、M _p) (6)

1≤M≤N (7)

$\underset{k=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{dm}}_k(i,j)\≥1---\left(8\right)$

Here, MG _{P, k}Be to comprise (p) individual task groups set candidate MGset _pK task groups.Dm _{P, k}(i, j) expression with move the related task group element from the i floor to the j floor.M _pBe included in p the task groups number in the task groups set candidate.(p) expression belongs to the quantity of task groups set candidate group's task groups set candidate.

Task groups set assessed value calculating section 5-2 carries out the calculating of RTT (terraced railway carriage or compartment back and forth once time) according to the traffic flow data of inferring and inferring of the operating efficiency of task groups set candidate.In this process, carry out load of terraced railway carriage or compartment and inferring of elevator number up and down.Calculating section 5-2 also carries out inferring of wait time and hourage according to the RTT that obtains.RTT is the time that terraced railway carriage or compartment once needs back and forth, according to the aviation value of this value, can know the time gap that arrives each floor, i.e. the aviation value of the service time interval in terraced railway carriage or compartment.In addition, also can assess the passengers quantity that time per unit may be carried.RTT is expressed as terraced railway carriage or compartment speed, the building story height, terraced railway carriage or compartment platform number stops terraced number of times, up and down the function of the time of elevator.Here, can think that the set of flow of traffic and task groups is variable value, terraced railway carriage or compartment speed, building story height, terraced railway carriage or compartment platform number are the fixed numbers that the specification sheets by the building provides.In addition, as every once the function of number of elevator up and down back and forth in terraced railway carriage or compartment, provide the number of times that stops ladder and time of elevator up and down.Further, every once the number of elevator up and down back and forth in terraced railway carriage or compartment is long-pending the providing of time gap that the time gap that arrived by the passenger and terraced railway carriage or compartment arrive.Therefore, the time gap that the passenger arrives is the function of traffic flow data, and the time gap that terraced railway carriage or compartment arrives is the function of RTT and task groups set.According to above explanation, RTT is shown below.

RTT(p、t)＝f(RTT(p、t)、TrafficFlow(t)、MGset _p) (9)

But

RTT(p、t)＝{rtt(p、1、t)、rtt(p、2、t)、.....、rtt(p、M _p、t)) (10)

Again, (p, k are to be assigned with task groups MG t) to rtt _{P, k}Terraced railway carriage or compartment for back and forth once, once finish the aviation value of the time of expense that this task groups is changed.In addition, TrafficFlow (t) is the traffic flow data of inferring at moment t, for example, as shown in the formula like that, schemes OD (t) and the passenger's of taking place in whole building incidence PassRate (t) represents with OD.

TrafficFlow(t)＝{OD(t)、PassRate(t)} (11)

OD figure OD (t) is the ratiometric row-column list that each floor gap of expression moves, and makes OD that (t) the ratiometric element for representing to move from i course j layer then has for i, j

OD(t)＝{OD(i、j、t)|i＝1、....、L、j＝1、.....、L} (12)

Here, OD when i=j (i, j, constraint condition t)=0 are arranged.

At this moment (p, k t) get the form of (7) formula, so can try to achieve numerical solution by repeated calculation because of RTT.

Fig. 6 represents to infer calculation control result's program operation chart, states its detailed situation below.

At step 3-1, and traffic flow data TrafficFlow (t) that input is inferred and task groups set candidate MGsetp (i, j).

At step 3-2, by TrafficFlow (t) according to following formula try to achieve the passenger generation from (i) layer to (j) layer probability P R (i, j, t).

PR(i、j、t)＝OD(i、j、t)PassRate(t) (13)

At step 3-3, provide the initial value RTT-init of RTT, with its substitution RTTold.

At step 3-4, calculate the ratio of each task groups generation frequency.With this than being called the task groups occurrence rate.This task groups occurrence rate is the function of the Total passenger of generation on task groups is all.

${\mathrm{MR}}_{p,k}\left(t\right)=F_{\mathrm{MR}}(\underset{i=1}{\overset{L}{\mathrm{\Σ}}}\underset{j=1}{\overset{L}{\mathrm{\Σ}}}\mathrm{PR}(i,j,t)\·{\mathrm{dm}}_{p,k}(i,j))---\left(14\right)$

Here, for example, when consideration is represented the model of each task groups with the ratio of all total riderships of task groups, function F _MRIn time, be expressed from the next out.

${\mathrm{MR}}_{p,k}\left(t\right)=\frac{(\underset{i=1}{\overset{L}{\mathrm{\Σ}}}\underset{j=1}{\overset{L}{\mathrm{\Σ}}}\mathrm{PR}(i,j,t)\·{\mathrm{dm}}_{p,k}(i,j))}{\underset{i=1}{\overset{L}{\mathrm{\Σ}}}\underset{j=1}{\overset{L}{\mathrm{\Σ}}}\mathrm{PR}(i,j,t)}---\left(15\right)$

At step 3-5,, calculate terraced railway carriage or compartment arrival interval CarArrive from RTTold for passenger from the i layer to the j layer _p(i, j, t).Arrival interval, ladder railway carriage or compartment is for the passenger from (i) layer to (j) layer, holds the time gap of the terraced railway carriage or compartment arrival of the task groups that service can be provided, and is tried to achieve by following formula.

$\frac{1}{\mathrm{CarArriv}{e}_p(i,j,t)}=\underset{k=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{dm}}_{p,k}(i,j)\frac{{\mathrm{MR}}_{p,k}\·\mathrm{Num}}{\mathrm{RTT}\_\mathrm{ol}{d}_k}---\left(16\right)$

Here, RTTold_j is and the element of the cooresponding RTTold of Mission_j (i) that cNum is the platform number in terraced railway carriage or compartment.

At step 3-6, number takes place in the average passenger who tries to achieve when arriving in the terraced railway carriage or compartment that each floor has been assigned with certain task groups.For example, order has been assigned with task groups MG _{P, k}The average passenger of terraced railway carriage or compartment when the upd direction arrives (i) layer number takes place is GP _{P, k}(i, upd, t) then can try to achieve this average passenger by following formula number takes place.

$\left\{\begin{array}{c}{\mathrm{GP}}_{p,k}(i,\mathrm{up},t)=\underset{j=i+1}{\overset{L}{\mathrm{\Σ}}}\mathrm{CarArriv}{e}_p(i,j,t)\·\mathrm{PR}(i,j,t)\·{\mathrm{dm}}_{p,k}(i,j)\\ {\mathrm{GP}}_{p,k}(i,\mathrm{down},t)=\underset{j=1}{\overset{i-1}{\mathrm{\Σ}}}\mathrm{CarArriv}{e}_p(i,j,t)\·\mathrm{PR}(i,j,t)\·{\mathrm{dm}}_{p,k}(i,j)\end{array}\right.---\left(17\right)$

Here, upd represents the direction of terraced railway carriage or compartment walking, the value of getting up (rising) or down (decline).When the upd=up direction, i＜j, when the upd=down direction, i＞j sues for peace to j.For the up direction of all i layers, the down direction, calculate this and.

At step 3-7, from average passenger number GP takes place _{P, k}(i, upd, t), the last elevator number of calculating (i) layer upd direction, following elevator number, the number in the terraced railway carriage or compartment, the load factor in terraced railway carriage or compartment.At first, when the upd direction, move to the superiors, when the down direction, move to orlop, elevator number in the calculating, following elevator number, the number in the terraced railway carriage or compartment, the load factor in terraced railway carriage or compartment from the superiors from orlop.

$\mathrm{LoadRat}{e}_{p,k}(i,\mathrm{upd},t)=\frac{(\mathrm{LastLoadNum}-\mathrm{Getof}{f}_{p,k}(i,\mathrm{upd},t)+{\mathrm{GP}}_{p,k}(i,\mathrm{upd},t))}{\mathrm{cNum}}---\left(18\right)$

Here, LoadRate _{P, k}(i, upd, t) is terraced railway carriage or compartment load factor, and LastLoadNum is the number in terraced railway carriage or compartment when in the past one deck sets out, GetOff _{P, k}(i, upd, t) is in the following elevator number of i layer in the upd direction.LastLoadNum is when upd=up, the number in the terraced railway carriage or compartment of (i-1) layer, or when upd=down, the number in the terraced railway carriage or compartment of (i+1) layer.

In addition, LoadOff _{P, k}(i, upd, t) is when upd=up, and all layer of layer from orlop to (i-1), to the mobile passenger's sum of (j) layer, or when upd=down, all layers from the superiors to the i+1 layer are to the mobile passenger's sum of (j) layer.In addition, about task groups k, because the number LoadNum in the terraced railway carriage or compartment of upd direction during from (i) layer _{P, k}(i, upd, t) can not surpass the staffing number in terraced railway carriage or compartment, so LoadNum _{P, k}(i, upd, t) can be tried to achieve by following formula.

LoadNum _p、k(i、upd、t)＝min(LoadRate _p、k(i、upd、t)、1)·CNum (19)

Here, (x is in x and y value y) to min, turns back to a little side's function.Again, (i) the elevator number on the upd direction of layer can be obtained by following formula.

GetOn _p、k(i、upd、t)

＝GP _p、k(i、upd、t))-{LoadRate _p、k(i、upd、t)·cNum-LoadNum _p、k(i、upd、t))

(20)

In step 3-8, try to achieve the probability that stops of each layer from the above-mentioned number of elevator up and down.That is, the ladder railway carriage or compartment stops when the one or more people of generation goes up elevator or following elevator.Therefore, although as long as we think that it is of equal value having the probability of passenger's generation and terraced railway carriage or compartment to stop probability less.Regard the above-mentioned number of elevator up and down as average elevator number up and down, we suppose this up and down the passenger of elevator arrive rule according to Pu Asong and take place, try to achieve on during the service intervals of terraced railway carriage or compartment elevator or down the people of elevator one people or the probability more than the people take place.That is, suppose when Pu Asong arrives rule that order group coefficient is G, the probability that is spaced apart s that the group of the G position passenger from (i) layer to (j) layer arrives is obeyed the exponential distribution of following formula.

$P_f(s,p,q)\left(t\right)=\frac{e^{-\frac{\mathrm{PR}(i,j,t)\·s}{G}}}{\mathrm{PR}(i,j,t)}---\left(21\right)$

Therefore, at service intervals CarArrive _p(i, j, t) between the probability come of group be expressed from the next.

$P_p(i,j,t)=1-e^{-\frac{\mathrm{PR}(i,j,t)\·\mathrm{CarArri}{\mathrm{ve}}_p(i,j,t)}{G}}---\left(22\right)$

Consideration can be by task groups at arrival (i) layer or from the group of (i) layer _k, provide the situation of service, the probability StR that task groups k stops in the upd direction at (i) layer _{P, k}(i, upd t) can be obtained by following formula.

$\left\{\begin{array}{c}{\mathrm{StR}}_{p,k}(i,\mathrm{up},t)=1-\underset{x=i+1}{\overset{L}{\mathrm{\Π}}}(1-P(i,x,t)\·{\mathrm{dm}}_{p,k}(i,x))\·\underset{y=1}{\overset{x-1}{\mathrm{\Π}}}(1-P(y,i,t)\·{\mathrm{dm}}_{p,k}(y,i))\\ {\mathrm{StR}}_{p,k}(i,\mathrm{down},t)=1-\underset{x=1}{\overset{i-1}{\mathrm{\Π}}}(1-P(i,x,t)\·{\mathrm{dm}}_{p,k}(i,x))\·\underset{y=x+1}{\overset{L}{\mathrm{\Π}}}(1-P(y,i,t)\·{\mathrm{dm}}_{p,k}(y,i))\end{array}\right.---\left(23\right)$

Here, x is the layer that will go from the passenger of i layer in the upd direction, and y is the starting layer that arrives the passenger of (i) layer in the upd direction.

At step 3-9, try to achieve the layer of elevator car counter-rotating and elevator car and walking, stop number of times from the probability that stops at each layer, to try to achieve the average travel distance of elevator car and on average stop number of times, the calculating elevator car is once time back and forth.At first, consider from the counter-rotating probability.For example,, regard as at (i) layer and stop the top counter-rotating probability of the direction counter-rotating under (i) course of the terraced railway carriage or compartment in walking up, and more than (i) layer non-stop probability.In addition, order is 1 at the above non-stop probability of (i) layer in the value of the superiors, when elevator car during from the superiors' backspace, can calculate non-stop probability more than (i) layer.Therefore, the terraced railway carriage or compartment that has been assigned with task groups k more than (i) layer at the non-stop probability NoStR of up direction _{P, k}(i, upd t) can be obtained by following formula.

NoStR _p、k(i、upd、t)＝StR _p、k(i+1、upd、t){1-StR _p、k(i+1、upd、t)} (24)

In addition, executing the task the terraced railway carriage or compartment of group k at the above probability RevR that reverses in the upd direction of (i) layer _{P, k}(i, upd t) can be provided by following formula.

RevR _p、k(i、upd、t)＝NoStR _p、k(i+1、upd、t)·StR _p、k(i、upd、t) (25)

More than, try to achieve the probability of occurrence of the walking mode (stopping layer and counter-rotating) in terraced railway carriage or compartment from formula (24) and formula (25), from the number of elevator up and down that obtains at step 3-7, can calculate in the time of the elevator up and down of each layer, can calculate the travel time that in each walking mode, needs in addition.For example, the terraced railway carriage or compartment that has been assigned with task groups k is from the counter-rotating of direction under (i) course, and (i, j t) can be obtained by following formula the travel time RT that reverses to direction on (j) course.

$\left\{\begin{array}{c}\mathrm{RT}(i,j,t)=\frac{\mathrm{Dis}(i,j)}{v}+A_1\&CenterDot;\underset{n=1}{\overset{j}{\mathrm{\&Sigma;}}}\mathrm{St}{R}_{p,k}(n,\mathrm{up},t)+A_2\underset{n=1}{\overset{j-1}{\mathrm{\&Sigma;}}}\{\mathrm{getO}{n}_{p,k}(n,\mathrm{up},t)+\mathrm{getOf}{f}_{p,k}(n+1,\mathrm{up},t)\}(i>j)\\ \mathrm{RT}(i,j,t)=\frac{\mathrm{Dis}(i,j)}{v}+A_1\&CenterDot;\underset{n=1}{\overset{j}{\mathrm{\&Sigma;}}}\mathrm{St}{R}_{p,k}(n,\mathrm{down},t)+A_2\underset{n=j+1}{\overset{i}{\mathrm{\&Sigma;}}}\{\mathrm{getO}{n}_{p,k}(n,\mathrm{down},t)+\mathrm{getOf}{f}_{p,k}(n-1,\mathrm{down},t)\}(i<j)\end{array}\right.---\left(26\right)$

Here, (i is that v is a terraced railway carriage or compartment speed, A from (i) layer distance to (j) layer j) to Dis ₁Be to stop once required acceleration and deceleration time, A ₂It is every time of elevator up and down that the passenger is required.Further,, by considering their probability of occurrence, and average, carry out the once required time totalRT of certain task groups about various walking modes _{P, k}(t) can be as shown in the formula calculating like that.

$\mathrm{toptalR}{T}_{p,k}\left(t\right)=\underset{i=1}{\overset{M-1}{\mathrm{\&Sigma;}}}\underset{j=i+1}{\overset{M}{\mathrm{\&Sigma;}}}\{\left(\mathrm{Rev}{R}_{p,k}(i,\mathrm{up},t)\right)\&CenterDot;\left(\mathrm{St}{R}_{p,k}(i,\mathrm{up},t)\right)\}\{\left(\mathrm{Rev}{R}_{p,k}(j,\mathrm{up},i)\right)\&CenterDot;\left(\mathrm{St}{R}_{p,k}(j,\mathrm{up},t)\right)\}\mathrm{RT}(i,j,t)$

$+\underset{i=2}{\overset{M}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{i-1}{\mathrm{\&Sigma;}}}\{\left(\mathrm{Rev}{R}_{p,k}(i,\mathrm{up},t)\right)\&CenterDot;\left(\mathrm{St}{R}_{p,k}(i,\mathrm{up},t)\right)\}\{\left(\mathrm{Rev}{R}_{p,k}(j,\mathrm{down},i)\right)\&CenterDot;\left(\mathrm{St}{R}_{p,k}(j,\mathrm{down},t)\right)\}\mathrm{RT}(i,j,t)---\left(27\right)$

In step 3-10, once required back and forth time of the elevator car that will try to achieve in step 3-9 is as new RTT substitution RTTnew.

In step 3-11, carry out the comparison of RTTnew and RTTold, if their difference is below threshold value, then advance to step 3-13, if this difference then advances to step 3-12 more than threshold value, result of calculation RTTnew substitution RTTold with current turns back to step 3-5.

At step 3-13, according to passenger's service intervals CarArrive _p(i, j t), calculate wait time, and stop probability calculation hourage according to each layer.

According to above program, can access the average latency, average hourage, terraced railway carriage or compartment load factor, elevator on each layer, following elevator numbers etc. are as control result's presumed value.

Below, the assessed value that we state in task groups set evaluation part 5-3 is calculated.

As stating, in the real time simulator part, can access the average latency, average hourage, terraced railway carriage or compartment load factor etc. are as control result's presumed value.Therefore, when the flow of traffic TrafficFlow (t) that infers takes place, select task groups set candidate MGset _pThe time assessed value can provide as follows.

If(MaxLoad(p、t)＜LoadThreshold)

E(p、t)＝K1·WaitTime(p、t)+K2·TravelTime(p、t) (28)

Else

E(p、t)＝∞

Here, (p is to gather candidate MGset from the flow of traffic TrafficFlow (t) and the task groups of inferring t) to MaxLoad _pIn time, calculate, LoadRate (k, i, maxim upd).LoadThreshold is the permissible value of the terraced railway carriage or compartment load of maximum, if this value is not less than 1, too much passenger is taken place then.(p t) is task groups set candidate MGset to E _pAssessed value.(p is to select task groups set candidate MGset t) to WaitTime _pThe time bed rearrangement building average latency, (p t) is the average hourage in bed rearrangement building to TravelTime.K1, K2 are respectively the weights of wait time and hourage.

Like this, (p, in the time of t), task groups set deciding section 5-4 selects E (p, t) the task groups set candidate MGset that becomes hour to definition assessed value E _pAs task groups set candidate MGset, be input to task groups storage area 6.Task groups storage area 6 is kept at the task groups set candidate MGset of input in the memory device.When upgrading, flow of traffic TrafficFlow (t) can carry out above process.

Below, when taking place, new platform calls out Call _NewThe time, select from MGset in task group selection part 7 platform is called out the task groups MG that service may be provided _kIn the time may providing service, select a plurality of task groups with a plurality of task groups.At this moment, if be not assigned with MG _kTerraced railway carriage or compartment, then in task set of dispense part 8, decision distributes MG _kTerraced railway carriage or compartment.As distribution method, for example can utilize following rule.

The candidate ladder railway carriage or compartment group who distributes=the do not distribute terraced railway carriage or compartment of any one task groups,

(if platform number=1 in the candidate ladder railway carriage or compartment group of distribution)

The unique terraced railway carriage or compartment in the candidate of the terraced railway carriage or compartment of Fen Peiing=the be included in distribution ladder railway carriage or compartment group then,

Otherwise, if (platform number＞1 in the candidate ladder railway carriage or compartment group of distribution)

Then may the earliest de novo platform be called out among the candidate of the terraced railway carriage or compartment=distribution of the Fen Peiing ladder railway carriage or compartment group made the terraced railway carriage or compartment of replying

Otherwise, if (platform number＜0 in the candidate ladder railway carriage or compartment group of distribution)

Then the terraced railway carriage or compartment of Fen Peiing=finish the earliest provides service, the terraced railway carriage or compartment that frees to the passenger relevant with the whole callings in the record from the task groups of distributing.

In task group selection part 7, whether decision exists is being assigned with the task groups MG that service may be provided _kTerraced railway carriage or compartment.In addition, in task set of dispense part 8, allocating task group MG _k, decision can be to Call _NewProvide the terraced railway carriage or compartment of service, in the terraced railway carriage or compartment that 9 decisions of call distribution part distribute.For example, can select the terraced railway carriage or compartment of distribution with following such method.When task group selection part 7 is selected a task groups, select to be assigned with this task groups MG _kTerraced railway carriage or compartment as the terraced railway carriage or compartment of distributing.When task group selection part 7 is selected a plurality of task groups, from the terraced railway carriage or compartment that has been assigned with these task groups, selection can be the earliest to new calling Call _NewMake the terraced railway carriage or compartment of replying as the terraced railway carriage or compartment of distributing.Perhaps, to occurent whole callings, the time that assessment may be replied, indexs such as service concluding time, this assessment also may be a gimmick of selecting the highest terraced railway carriage or compartment.

By as above constitute the optimum management method and apparatus of elevator group like that, can be flow of traffic TrafficFlow (t), the task groups of selecting to optimize is gathered, task groups set according to this optimization, by controlling in the operation in 7 pairs of terraced railway carriage or compartments of operation control part, terraced railway carriage or compartment, just can realize the operation optimized, and call distribution calculates also simply than existing method of calculating, can carry out more high-revolving calculating.

Example 2

Our explanation has optimum management method and apparatus with the elevator group of example 1 different formations as example 2 of the present invention.In the formation of example 2, replace the task groups set assessed value calculating section 5-2 of example 1, be provided with real time simulator part 5-5.Because other parts are identical with example 1, so no longer describe here.Fig. 7 is the task groups set generating portion 5 in example 2.Here, real time simulator part 5-5 carries out inferring the operating efficiency of task groups set candidate with the optimum management method simulator of elevator group.This simulator is the traffic flow data and the task groups set candidate of inferring in input, on the simulator of output wait time and hourage etc., as the call distribution algorithm, have task groups and select part 7, task groups distribution portion 8, the simulator of the function of call distribution part 9 for example has formation shown in Figure 8.

In Fig. 8,5-5-1 is according to the flow of traffic of inferring for passenger's Behavior modeling part, and the passenger's behavior that occurs to mobile end from the passenger is simulated.Ladder railway carriage or compartment action simulation part 5-5-2 stops the walking in terraced railway carriage or compartment, and the terraced railway carriage or compartment action of the state of door etc. is simulated.Task groups selection function emulation part 5-5-3 holds with task groups and selects the same function of part 7.Task groups distribution function emulation part 5-5-4 holds the function same with task groups distribution portion 8.Call distribution functional simulation part 5-5-5 holds the function same with call distribution part 9.Elevator group controller calculating section 5-5-6 as a result calculates the elevator group controller result of wait time and hourage etc. from the analog result of passenger's Behavior modeling part 5-5-1 and terraced railway carriage or compartment action simulation part 5-5-2, exports as task groups candidate assessed value.

By the above optimum management method and apparatus that constitutes elevator group like that, also can gather candidate by example 1 and carry out more accurate assessment task groups, for flow of traffic, the selection of the task groups set that can be optimized, by task groups set according to this optimization, control in the operation in 7 pairs of terraced railway carriage or compartments of operation control part, terraced railway carriage or compartment, can realize the terraced railway carriage or compartment operation of optimizing, and call distribution is calculated also simple than existing method of calculating, can calculate more at high speed.

Example 3

We have stated the optimum management method and apparatus with the different elevator group that constitute of example 1,2, as other example of the present invention.The formation of this example is on the formation of example 1 or example 2, have logger task group set and the traffic flow data of inferring between the task groups collective database that concerns.The whole pie graph of this example as shown in Figure 9.Because except part 11 and task groups collective database 12 were selected in the task groups set, other parts were all identical with example 1,2, so no longer describe here in Fig. 9.With following such data storage in task groups collective database 12.

data _q＝{TrafficFlow _q，MGset _q} (q＝1，…，Q) (29)

Here, data _qBe q storage data of data bank.Q is the quantity that is stored in the data in the data bank.TrafficFlow _qBe and the individual relevant flow of traffic of storage data of q, MGset _qBe for TrafficFlow _qThe task groups set of optimizing.Use this data bank,, determine task groups set MGset as follows for the flow of traffic TrafficFlow (t) that infers.

With the traffic flow data TrafficFlow (t) that infers, infer part 4 from flow of traffic and be input to task groups set when selecting part 11, from the storage data of task groups collective database 12, retrieval is held and the consistent TrafficFlow of traffic flow data TrafficFlow (t) that infers _qData data _qIf there is data _q, then with MGset _qAs task groups set MGset, be input to task groups set storage area 6, carry out the optimum management method of elevator group.If in task groups collective database 12, there is not data _q, then identical with example 1 or 2, on task groups set generating portion 5, make task groups set MGset.At this moment, MGset is input to task groups set storage area 6, not only carries out the optimum management method of elevator group, and as follows TrafficFlow (t) and MGset are stored in the task groups collective database 12, as new data.

data(R)＝{TrafficFlow _(Q+1)＝TrafficFlow(t)，MGset _(Q+1)＝MGset} (i＝1，…，Q+1)

(30)

By the above optimum management method and apparatus that constitutes elevator group like that, with example 1,2 also can carry out the selection of task groups set more at high speed, by task groups set according to this optimization, operation in 7 pairs of terraced railway carriage or compartments of operation control part, terraced railway carriage or compartment is controlled, the terraced railway carriage or compartment operation that can realize optimizing, and call distribution calculates also simply than existing method of calculating, can calculate more at a high speed.

Example 4

We state the optimum management method and apparatus of the elevator group different with example 3, as example of the present invention.The formation of this example is that part 11 and task groups collective database 12 are selected in the task groups set of replacement example 3, has the neural task groups set selection part of carrying out the selection of task groups set with neural network.

The formation of this example as shown in figure 10.In Figure 10, since all identical except part 13 is selected in neural task groups set with example 3, so no longer describe here.It is that flow of traffic TrafficFlow (t) and the task groups that study is inferred gathered the neural network that concerns between the MGset that part 13 is selected in neural task groups set.The formation of neural network as shown in figure 11.The traffic flow data of inferring is input to neural task groups set selects part 13 and neural task groups to select administrative section 13-1 with this quantitative data input neural network 1 3-2.Neural network 1 3-2 has the structure of Figure 12, and each element of the flow of traffic TrafficFlow (t) that infers is input to input layer.In Figure 12, o _r(t) be input data TrafficFlow (t) for moment t, r the neuronic output valve of output layer of neural network 1 3-2, R is the task groups set MGset that is being learnt in neural network _rThe neuronic quantity of quantity output layer, the set LMGset that is gathered by the task groups learn can be expressed as follows.

LMGset＝{MGset _r：r＝1、...、R} (31)

In advance, make for the TrafficFlow that imports _y, with the task groups set LMGset that optimizes _yCooresponding output layer neuron output o _yOr o (t)=1 _r(t)=0 learning neural network like that is input to task groups set selective filter 13-3 with this output.The threshold filter that task groups set selective filter 13-3 represents according to following formula is selected task groups on the output valve of neural network.

$\left\{\begin{array}{cc}{F}_r\left(t\right)=1& (o_r\left(t\right)\&GreaterEqual;\mathrm{TH})\\ F_r\left(t\right)=0& (o_r\left(t\right)<\mathrm{TH})\end{array}\right.---\left(32\right)$

Here, F _r(t) be for o _rThe value of threshold filter (t).At this moment, according to following rule, the value of decision task groups set selective filter.

$\left\{\begin{array}{cc}\mathrm{if}(\underset{r=1}{\overset{R}{\mathrm{\&Sigma;}}}{F}_r=0)& \mathrm{then}\\ & FileterO\left(t\right)=\mathrm{noMGset}\\ \mathrm{elseif}(\underset{r=1}{\overset{R}{\mathrm{\&Sigma;}}}{F}_r>1)& \mathrm{then}\\ & \left\{\begin{array}{c}\mathrm{FileterO}\left(t\right)=\mathrm{pluralSelection}\\ O_{\mathrm{FILTER}}\left(t\right)=\{F_r\left(t\right):r=1,...,R\}\end{array}\right.\\ \mathrm{else}& \\ & \mathrm{FileterO}\left(t\right)=\underset{r=1}{\overset{R}{\mathrm{\&Sigma;}}}(F_r\left(t\right)\&CenterDot;r)\end{array}\right.---\left(33\right)$

Here, FilterO (t) is the output in the threshold filter of moment t, the number p and the MGset of its value representation task groups set candidate _pIn addition, noMGset represents not have the set of appropriate tasks group, and pluralSelection represents to have a plurality of task groups set candidates of selecting.In addition, O _FILTER(t) be the set of filter output.With FilterO (t) and O _FILTER(t) offer neural task groups and select administrative section 13-1.If the value of FilterO (t) is not equal to noMGset, then neural task groups selects administrative section 13-1 with MGset _FilterO(t) output to task groups set storage area, the selection course of the group set that ends task as task groups set MGset.When the value of FilterO (t) equals noMGset, the traffic flow data TrafficFlow (t) that infers is input to task groups set generating portion 5.Task groups set generating portion 5 generates the task groups set MGset that optimizes for the traffic flow data TrafficFlow (t) that infers, and gives neural task groups selection administrative section 13-1 with it.Neural task groups is selected administrative section 13-1 that task groups is gathered MGset and is outputed to task groups set storage area 6, and with TrafficFlow (t) and task groups set MGset as the new learning data newLdatal (t) that provides by following formula, give neural network learning part 13-4.

newLdata(t)＝{TrafficFlow(t)、MGset} (34)

Neural network learning part 13-4 is appended to new learning data newLdatal (t) on the learning data set Ldata that is stored in learning data set storage area 13-5.Learning data set Ldata can be provided by following formula.

LData＝{Ldata ₁、Ldata ₂、....、LData _Y} (35)

Ldata _y＝{TrafficFlow _y、MGset _y} (36)

Here, V is the quantity that is stored in the learning data of learning data set storage area 13-5.Ldata _yBe y learning data of expression, its element is by traffic flow data TrafficFlow _yThe most suitable its task groups set MGset _yForm.In addition, if the task groups of the study identical set MGset with the element M Gset of newLdatal (t) _rBe not included among the set LMGset of the task groups set of learning, then neural network learning part 13-4 makes the neuronic quantity of output layer of neural network 1 3-2 increase by 1.In addition, make the traffic flow data TrafficFlow of neural network 1 3-2 learning records on learning data set Ldata _yWith task groups set MGset _yBetween relation.

By the above optimum management method and apparatus that constitutes elevator group like that, also can carry out the selection that task groups is gathered more at high speed and with littler memory-size with example 3, by task groups set according to this optimization, carry out the control of terraced railway carriage or compartment operation at terraced railway carriage or compartment operation control part 7, the terraced railway carriage or compartment operation that just can realize optimizing, and call distribution is calculated also simple than existing method of calculating, can calculate more at high speed.

As mentioned above, the optimum management method and system of elevator group of the present invention is by in being provided with the elevator group in many terraced railway carriage or compartments, detect the state of elevator and platform device, infer flow of traffic according to this information, make the candidate of a plurality of task groups set, for the traffic flow data of inferring, calculate the assessed value of the task groups set candidate that generates, carry out the assessment of task groups set according to this assessed value, according to this assessment result, the task groups set that decision is optimized stores this task groups set, according to the status information of described detected elevator and platform device, at this moment be subordinated to and select the task groups set that needs in the task groups of task groups set of storage, this task groups is distributed to terraced railway carriage or compartment,, constitute for terraced railway carriage or compartment like that the platform call distribution according to this allocation situation, for traffic flow data, just can realize the operation optimized, and call distribution calculates also simply than existing method of calculating, can calculate more high-revolvingly.

In addition, if optimum management method and system with elevator group of the present invention, then by carry out assessment with real time simulator to task groups set candidate, for traffic flow data, just can realize the operation optimized, and call distribution is calculated also simple than existing method of calculating, can calculate more at high speed.

Further, if with the optimum management method and system of elevator group of the present invention, data bank then by concerning between the flow of traffic that has the set of store tasks group and infer, generation can determine the effect of the task groups set optimized at high speed.

In addition, further, if with the optimum management method and system of elevator group of the present invention, then the neural network by concerning between the flow of traffic that has the set of learning tasks group and infer produces the effect that can determine the task groups set of optimization by littler computer installation more at high speed.

Claims (9)

1. the optimum management method of elevator group of a plurality of elevator car of operation, an element on the row-column list that concerns between floor and the arrival floor that sets out that it is characterized in that the expression elevator car may be served is called task unit, the combination of the task unit that an elevator once may be served is called task groups, to be called the task groups set for the set of all task groups of preparing of elevator group, thereby move elevator expeditiously by elevator group is dynamically distributed in this task groups set.

2. the optimum management method of elevator group of record in the claim 1, its feature is to infer occurent flow of traffic, for the flow of traffic of inferring, the task groups that decision is optimized, the task groups that will belong to this task groups set is dynamically distributed to a plurality of elevators.

3. the optimum management method of elevator group of record in the claim 1, its feature is to infer occurent flow of traffic, for the flow of traffic of inferring, carry out the assessment of task groups set, the task groups set that decision is optimized, the task groups that will belong to the task groups set of this optimization is dynamically distributed to a plurality of elevators.

4. the optimum management method of elevator group of record in the claim 1, its feature is to infer occurent flow of traffic, for the flow of traffic of inferring, by real time simulator task groups set is assessed, the task groups set that decision is optimized, the task groups that will belong to the task groups set of this optimization is dynamically distributed to a plurality of elevators.

5. the optimum management method of elevator group of record in the claim 1, its feature is that the relation of the flow of traffic that will once obtain and task groups set is stored in the data bank, the result that infers from this data bank and flow of traffic, the task groups set that decision is optimized, the task groups that will belong to the task groups set of this optimization is dynamically distributed to a plurality of elevators.

6. the optimum management method of elevator group of record in the claim 1, its feature is the relation that makes neural network learning flow of traffic and task groups, from neural network learning to the result, the task groups set that decision is optimized, the task groups that will belong to the task groups set of this optimization is dynamically distributed to a plurality of elevators.

7. the optimum management system of elevator group of a plurality of elevator car of operation, its feature is to have

(a) terraced railway carriage or compartment information detection section, it detects the state of elevator and platform device,

(b) flow of traffic is inferred part, and it infers flow of traffic according to the information that obtains from described terraced railway carriage or compartment information detection section,

(c) task groups set candidate generating portion, it makes the candidate of a plurality of task groups set,

(d) real time simulator, it calculates the assessed value of the task groups set that generates in described task groups set candidate generating portion for infer the traffic flow data of inferring that part obtains from described flow of traffic,

(e) task groups set evaluation part, it carries out the assessment of task groups set according to the assessed value that obtains from described real time simulator,

(f) task groups set deciding section, it is according to the result of described task groups set evaluation part, and the task groups that decision is optimized is gathered,

(g) task groups set storage area, it will store in the task groups set of described task groups set deciding section decision,

(h) task groups selection part, its is subordinated to the task groups that selection needs at this moment in the task groups that is stored in the task groups set in the described task groups set storage area according to the information that obtains from described terraced railway carriage or compartment information detection section,

(i) task groups distribution portion, it will distribute to terraced railway carriage or compartment in the task groups of described task groups selection portion component selections,

(j) call distribution part, it gives terraced railway carriage or compartment according to the allocation situation of the task groups that determines in described task groups distribution portion with the call distribution of platform,

(k) terraced railway carriage or compartment control part, it is controlled terraced railway carriage or compartment according to the allocation situation of call distribution part.

8. the optimum management system of elevator group of record in the claim 7, its feature have the data bank of task groups set and part is selected in the task groups set of the task groups set optimized according to the Information Selection that is stored in the described data bank.

9. the optimum management system of elevator group of record in the claim 7, its feature is to have the flow of traffic of inferring by study and is the neural network of the relation between the task groups set of optimizing to this flow of traffic, selects the neural task groups set of the task groups set optimized to select part.

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